Summary

Dataset 1

Experiments excluded

Mask

Get figure file: figures/preliminary_dset-1_figure-mask.png

Peak coordinates

Get figure file: figures/preliminary_dset-1_figure-static.png
Get figure file: figures/preliminary_dset-1_figure-legend.png

Explorer

Meta-Analysis

Estimator

Parameters use to fit the meta-analytic estimator.

Corrector

Parameters use to fit the corrector.

Corrected meta-analytic map: z_corr-FDR_method-indep

Explorer

The following figure provides an interactive window to explore the meta-analytic map in detail.

Slice viewer

This panel shows the the corrrected meta-analytic map.

Get figure file: figures/corrector_figure-static.png

Diagnostics

Target image: z_corr-FDR_method-indep

Significant clusters

    X Y Z Peak Stat Cluster Size (mm3)
Tail Cluster ID          
Positive 1 -48.00 -76.00 4.00 5.13 6608
1a -48.00 -66.00 4.00 4.39
1b -38.00 -78.00 2.00 3.85
1c -46.00 -66.00 -6.00 3.57
2 46.00 -70.00 -4.00 4.97 24888
2a 50.00 -60.00 -4.00 4.96
2b 50.00 -62.00 4.00 4.96
2c 34.00 -50.00 -14.00 4.79
3 -54.00 -50.00 18.00 4.96 5704
3a -62.00 -46.00 12.00 4.39
3b -54.00 -46.00 8.00 4.39
3c -54.00 -56.00 22.00 3.85
4 38.00 26.00 -2.00 4.79 11464
4a 48.00 10.00 38.00 3.85
4b 52.00 14.00 24.00 3.85
4c 52.00 26.00 14.00 3.85
5 -36.00 18.00 -4.00 4.61 6240
5a -44.00 24.00 -16.00 4.13
5b -34.00 20.00 4.00 3.57
5c -50.00 36.00 -6.00 3.27
6 -42.00 -58.00 -20.00 4.13 3296
6a -34.00 -54.00 -16.00 3.85
6b -46.00 -62.00 -18.00 3.57
6c -34.00 -58.00 -18.00 3.57
7 -52.00 30.00 8.00 3.27 680
7a -48.00 22.00 14.00 2.29
7b -52.00 28.00 0.00 1.95
7c -50.00 20.00 4.00 1.95
8 -26.00 -2.00 56.00 3.27 1800
8a -30.00 2.00 46.00 3.27
8b -30.00 -4.00 56.00 2.63
8c -34.00 4.00 54.00 2.29
9 -4.00 -88.00 2.00 3.27 640
9a -6.00 -92.00 12.00 1.95
10 2.00 58.00 10.00 3.27 1168
10a 4.00 50.00 12.00 2.63
10b -4.00 60.00 12.00 2.29
10c 8.00 54.00 12.00 2.29
11 26.00 0.00 -20.00 2.96 344
12 -6.00 42.00 -8.00 2.96 760
12a -2.00 48.00 -12.00 2.63
13 -36.00 -38.00 48.00 2.96 272
14 -8.00 -14.00 34.00 2.63 320
15 -24.00 0.00 -14.00 2.63 504
15a -20.00 -6.00 -18.00 2.29
15b -20.00 0.00 -12.00 2.29
16 -54.00 8.00 -22.00 2.63 560
16a -54.00 10.00 -30.00 1.95
16b -48.00 8.00 -24.00 1.95
17 44.00 -66.00 20.00 2.63 216
17a 42.00 -68.00 28.00 2.29
18 30.00 -90.00 24.00 2.63 208
19 30.00 -4.00 52.00 2.63 240
20 -12.00 -32.00 -6.00 2.63 152
21 -24.00 -54.00 -12.00 2.63 128
22 -2.00 10.00 52.00 2.63 528
22a 6.00 8.00 50.00 2.29
23 14.00 -18.00 2.00 2.63 144
24 0.00 -54.00 28.00 2.63 472
24a -6.00 -60.00 28.00 1.95
25 36.00 -32.00 46.00 2.63 472
25a 38.00 -28.00 54.00 2.63
25b 34.00 -32.00 42.00 2.29
25c 42.00 -32.00 54.00 2.29
26 8.00 -90.00 24.00 2.29 104
27 -48.00 10.00 -12.00 2.29 104
28 -16.00 6.00 -6.00 2.29 184
29 54.00 -40.00 48.00 2.29 80
30 30.00 -88.00 16.00 2.29 192
31 -40.00 6.00 32.00 1.95 112

Label map: positive tail

Get figure file: figures/diagnostics_tail-positive_figure.png

FocusCounter

The FocusCounter analysis characterizes the relative contribution of each experiment in a meta-analysis to the resulting clusters by counting the number of peaks from each experiment that fall within each significant cluster.

The heatmap presents the relative contributions of each experiment to each cluster in the thresholded map. There is one row for each experiment, and one column for each cluster, with column names being PostiveTail/NegativeTail indicating the sign (+/-) of the cluster's statistical values. The rows and columns were re-ordered to form clusters in the heatmap.

Heatmap: positive tail

Methods

We kindly ask to report results preprocessed with this tool using the following boilerplate.

A multilevel kernel density (MKDA) meta-analysis \citep{wager2007meta} was performed was performed
with NiMARE 0.6.0+6.g55f7ea1 (RRID:SCR_017398; \citealt{Salo2023}), using a(n) MKDA kernel. An MKDA
kernel \citep{wager2007meta} was used to generate study-wise modeled activation maps from
coordinates. In this kernel method, each coordinate is convolved with a sphere with a radius of
10.0 and a value of 1. For voxels with overlapping spheres, the maximum value was retained. Summary
statistics (OF values) were converted to p-values using an approximate null distribution. The input
dataset included 1999 foci from 228 experiments. False discovery rate correction was performed with
the Benjamini-Hochberg procedure \citep{benjamini1995controlling}.

Bibliography

@article{Salo2023,
  doi = {10.52294/001c.87681},
  url = {https://doi.org/10.52294/001c.87681},
  year = {2023},
  volume = {3},
  pages = {1 - 32},
  author = {Taylor Salo and Tal Yarkoni and Thomas E. Nichols and Jean-Baptiste Poline and Murat Bilgel and Katherine L. Bottenhorn and Dorota Jarecka and James D. Kent and Adam Kimbler and Dylan M. Nielson and Kendra M. Oudyk and Julio A. Peraza and Alexandre Pérez and Puck C. Reeders and Julio A. Yanes and Angela R. Laird},
  title = {NiMARE: Neuroimaging Meta-Analysis Research Environment},
  journal = {Aperture Neuro}
}
@article{benjamini1995controlling,
  title={Controlling the false discovery rate: a practical and powerful approach to multiple testing},
  author={Benjamini, Yoav and Hochberg, Yosef},
  journal={Journal of the Royal statistical society: series B (Methodological)},
  volume={57},
  number={1},
  pages={289--300},
  year={1995},
  publisher={Wiley Online Library},
  url={https://doi.org/10.1111/j.2517-6161.1995.tb02031.x},
  doi={10.1111/j.2517-6161.1995.tb02031.x}
}
@article{wager2007meta,
  title={Meta-analysis of functional neuroimaging data: current and future directions},
  author={Wager, Tor D and Lindquist, Martin and Kaplan, Lauren},
  journal={Social cognitive and affective neuroscience},
  volume={2},
  number={2},
  pages={150--158},
  year={2007},
  publisher={Oxford University Press},
  url={https://doi.org/10.1093/scan/nsm015},
  doi={10.1093/scan/nsm015}
}